Using Gemini 3.5 Flash on Google AI Studio

Implementation guide · Gemini 3.5 · Google DeepMind

Serverless

Google AI Studio exposes Gemini 3.5 Flash through model ID gemini-3.5-flash. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

1
Create an account at Google AI Studio and generate an API key.
2
Use the Google AI Studio SDK or REST API to call gemini-3.5-flash — see the documentation for request format.
3
You'll be billed $1.50/1M input, $9.00/1M output tokens. See full pricing.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install google-genai

API key

GOOGLE_API_KEY

Model ID

gemini-3.5-flash

Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".

import os
from google import genai

client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello"
)
print(response.text)

Pricing on Google AI Studio

Type	Price (per 1M)
Input tokens	$1.50
Output tokens	$9.00

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsCode ExecutionPrompt CachingBatch APIAudio

About Gemini 3.5 Flash

Gemini 3.5 Flash is Google DeepMind's generally available Flash model for sustained frontier-level performance on agentic and coding tasks. It supports multimodal inputs, native thinking, tool and function calling, structured outputs, code execution, search grounding, batch processing, and long contexts up to 1M tokens.

Full model details →

Model Specs

Released2026-05-19

Context1.05m

ArchitectureDecoder Only

Knowledge cutoff2025-01